Predictors of Performance of Students from the Canadian Memorial Chiropractic College on the Licensure Examinations of the Canadian Chiropractic Examining Board
Bibliographic record
Abstract
Lawson and Till 1Lawson DM Till H Predictors of performance of students from the Canadian Memorial Chiropractic College on the licensure examinations of the Canadian Chiropractic Examining Board.J Manipulative Physiol Ther. 2006; 29: 566-569Google Scholar conclude “the admissions interview is not a predictor of success” on various outcome measures yet fail to offer any data in their article to inform the reader or allow such a conclusion. They give a purpose of their study as being the determination of whether "the Canadian Memorial Chiropractic College [CMCC] structured admissions interview and other outcomes measures predict success" on the Canadian external licensure examination. The reader may thus reasonably expect to see data of the admissions interview in addition to the reported data such as Grade Point Average. In the absence of either summary data or a table identifying the elements within the structured interview, the authors can only offer an invalid conclusion. The absence of reported data should but does not prevent the authors making the unsubstantiated statement in their discussion that “none of the noncognitive characteristics used in the admissions process at CMCC were identified as predictors of success on the CCEB examinations.” Apart from stating that “appropriate noncognitive qualities (are) required” and admitting to a “lack of reliable and valid processes…to identify the noncognitive qualities of…applicants,” they fail to provide any description of the noncognitive components of the CMCC admissions process. The reader is thus forced to presume that these include a structured interview with no knowledge of the content or structure of that interview. Quite simply, the claimed lack of any predictive value of the admission interview could be due to either poor quality content of the interview or poor processes to accord ranking or other outcome measures. In the absence of the data, the reader is unable to make their own interpretation or indeed replicate the processes, both being strong indicators of weak research methodology and immature reporting. Reply to LetterJournal of Manipulative & Physiological TherapeuticsVol. 30Issue 2PreviewDoctor Till and I would like to thank the reader for bringing this matter to our attention. The reader is correct in stating that the data on the admissions interview should have been included with the other data. Because of the low correlation of the admissions interview to outcomes data from both the Canadian Memorial Chiropractic College (CMCC) and Canadian Chiropractic Examining Board (CCEB) and its poor prediction as based on the regression analysis, the values for the admissions interview were left out of the article. Full-Text PDF
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".